ISTQB CT-GenAI Practice Exam: 25 Sample Questions with Detailed Explanations

Practice exams are essential for CT-GenAI preparation. They help you understand question formats, identify knowledge gaps, calibrate your timing, and build confidence. This practice exam contains 25 questions designed to mirror the real CT-GenAI exam in difficulty and topic distribution.

The CT-GenAI exam contains 40 questions to be completed in 60 minutes, requiring 26 correct answers (65%) to pass. This practice exam gives you a realistic sample covering all syllabus chapters with appropriate weighting.

How to Use This Practice Exam

For maximum benefit, approach this practice exam as you would the real exam:

Set a timer: Allocate 37-40 minutes for 25 questions (proportional to 60 minutes for 40 questions).

No external resources: Don't look up answers during the practice. Note questions to review afterward.

Read carefully: Many wrong answers come from misreading questions, not lack of knowledge.

Answer everything: There's no penalty for guessing. Don't leave questions blank.

Review thoroughly: After completing, review explanations for both correct and incorrect answers.

Question Distribution

This practice exam follows CT-GenAI syllabus weighting:

Topic	Approximate Questions
Chapter 1: Fundamentals	5 questions
Chapter 2: Prompt Engineering	8 questions
Chapter 3: Risks and Ethics	6 questions
Chapter 4: AI Applications	4 questions
Chapter 5: Adoption	2 questions

Questions vary in difficulty:

• Easy (K1-K2): Direct recall and understanding
• Medium (K2-K3): Application and analysis
• Hard (K3): Scenario-based analysis and evaluation

Exam-Taking Strategies

First Pass Strategy

1. Read each question carefully, noting key words like "MOST," "BEST," "NOT," or "EXCEPT"
2. Answer questions you're confident about immediately
3. Flag uncertain questions for review
4. Don't spend more than 2 minutes on any question in the first pass

Managing Difficult Questions

When stuck:

• Eliminate obviously wrong answers first
• Look for ISTQB-specific terminology in remaining options
• Consider which answer best aligns with CT-GenAI principles
• If still unsure, make your best guess and move on

Time Management

For 25 questions in 38 minutes:

• Target 90 seconds per question average
• Check progress at question 12 (should be around 18 minutes)
• Reserve 3-5 minutes for review at the end

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Practice Exam Questions

Take the 25-question practice exam below. After completing, scroll down for score interpretation and next steps.

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Score Interpretation

After completing the practice exam, interpret your score:

20-25 Correct (80-100%)

Assessment: Excellent preparation. You have strong command of CT-GenAI concepts.

Next steps:

• Review any questions you missed to fill remaining gaps
• Consider taking the real exam soon while knowledge is fresh
• Focus on maintaining knowledge through continued practice with AI tools

16-19 Correct (65-79%)

Assessment: Passing range, but some knowledge gaps exist.

Next steps:

• Analyze which topics had the most wrong answers
• Review corresponding syllabus chapters
• Take another practice exam after targeted study
• Don't rush to the real exam; ensure consistent passing scores on practice

13-15 Correct (52-64%)

Assessment: Below passing threshold. Significant preparation still needed.

Next steps:

• Identify your weakest topics from the results
• Dedicate focused study time to weak areas
• Review foundational concepts if fundamentals questions were missed
• Retake practice exams after additional study

Below 13 Correct (Under 52%)

Assessment: Substantial preparation required before exam readiness.

Next steps:

• Return to systematic syllabus study rather than practice exams
• Ensure you understand AI fundamentals before advanced topics
• Consider additional resources if current materials aren't effective
• Practice hands-on with AI tools to reinforce conceptual learning

Next Steps After Practice

Regardless of your score, these activities strengthen preparation:

Review Wrong Answers

For each wrong answer:

1. Read the explanation carefully
2. Identify why your choice was incorrect
3. Note the correct concept or principle
4. Find corresponding content in your study materials
5. Create a flashcard or note for review

Identify Patterns

Look for patterns in your mistakes:

• Are errors concentrated in specific topics?
• Are you misreading questions or missing keywords?
• Are scenario questions harder than definition questions?
• Are you running out of time?

Address patterns with targeted practice.

Additional Practice

After addressing gaps:

• Take additional practice exams
• Practice with different question sources
• Time yourself to ensure exam-day readiness
• Aim for consistent scores above 75% before scheduling the real exam

Hands-On Practice

Reinforce learning with practical application:

• Practice prompt engineering with real AI tools
• Generate test cases and evaluate quality
• Experiment with different prompt structures
• Apply risk awareness when reviewing AI outputs

Schedule Your Exam

When you're consistently scoring 75%+ on practice exams:

• Schedule the real exam within 1-2 weeks
• Don't wait until you feel 100% ready. Confidence comes from passing, not from endless preparation
• The deadline creates productive urgency for final review

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Topic Review Quick Reference

Use this reference to review specific topics based on practice exam results:

If You Missed Fundamentals Questions

Review:

• Definition of generative AI vs. traditional AI
• How LLMs generate responses (token by token, probability-based)
• Non-deterministic nature of AI outputs
• Context windows and their limitations
• Knowledge cutoff concept

Key concepts: hallucination, token, inference, temperature, context window

If You Missed Prompt Engineering Questions

Review:

• CRISP framework (Context, Role, Instructions, Scope, Personalization)
• Few-shot learning (providing examples in prompts)
• Iterative refinement process
• Context management strategies
• Common prompt engineering mistakes

Practice: Create prompts for test case generation, automation scripts, and defect reports

If You Missed Risks and Ethics Questions

Review:

• Hallucination causes and detection strategies
• Bias sources and mitigation approaches
• Data privacy requirements and prohibited data types
• Security implications of AI-generated code
• Human oversight requirements and accountability

Key principle: Default to skepticism and verification, not trust

If You Missed AI Applications Questions

Review:

• AI applications across testing lifecycle
• Test case generation approaches
• Automation script assistance
• Defect management support
• When AI is and isn't appropriate for testing tasks

If You Missed Adoption Questions

Review:

• Readiness assessment dimensions
• Maturity model levels
• Phased implementation approach
• Governance framework components
• Success measurement metrics

Key principle: Pilot before scaling, governance from the start

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Frequently Asked Questions

Frequently Asked Questions (FAQs) / People Also Ask (PAA)